a b s t r a c tContext: Variability management (VM) is one of the most important activities of software product-line engineering (SPLE), which intends to develop software-intensive systems using platforms and mass customization. VM encompasses the activities of eliciting and representing variability in software artefacts, establishing and managing dependencies among different variabilities, and supporting the exploitation of the variabilities for building and evolving a family of software systems. Software product line (SPL) community has allocated huge amount of effort to develop various approaches to dealing with variability related challenges during the last two decade. Several dozens of VM approaches have been reported. However, there has been no systematic effort to study how the reported VM approaches have been evaluated. Objective: The objectives of this research are to review the status of evaluation of reported VM approaches and to synthesize the available evidence about the effects of the reported approaches. Method: We carried out a systematic literature review of the VM approaches in SPLE reported from 1990s until December 2007. Results: We selected 97 papers according to our inclusion and exclusion criteria. The selected papers appeared in 56 publication venues. We found that only a small number of the reviewed approaches had been evaluated using rigorous scientific methods. A detailed investigation of the reviewed studies employing empirical research methods revealed significant quality deficiencies in various aspects of the used quality assessment criteria. The synthesis of the available evidence showed that all studies, except one, reported only positive effects. Conclusion: The findings from this systematic review show that a large majority of the reported VM approaches have not been sufficiently evaluated using scientifically rigorous methods. The available evidence is sparse and the quality of the presented evidence is quite low. The findings highlight the areas in need of improvement, i.e., rigorous evaluation of VM approaches. However, the reported evidence is quite consistent across different studies. That means the proposed approaches may be very beneficial when they are applied properly in appropriate situations. Hence, it can be concluded that further investigations need to pay more attention to the contexts under which different approaches can be more beneficial.

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a b s t r a c tContext: Aspect-oriented programming (AOP) promises to improve many facets of software quality by providing better modularization and separation of concerns, which may have system wide affect. There have been numerous claims in favor and against AOP compared with traditional programming languages such as Objective Oriented and Structured Programming Languages. However, there has been no attempt to systematically review and report the available evidence in the literature to support the claims made in favor or against AOP compared with non-AOP approaches.Objective: This research aimed to systematically identify, analyze, and report the evidence published in the literature to support the claims made in favor or against AOP compared with non-AOP approaches. Method: We performed a systematic literature review of empirical studies of AOP based development, published in major software engineering journals and conference proceedings. Results: Our search strategy identified 3307 papers, of which 22 were identified as reporting empirical studies comparing AOP with non-AOP approaches. Based on the analysis of the data extracted from those 22 papers, our findings show that for performance, code size, modularity, and evolution related characteristics, a majority of the studies reported positive effects, a few studies reported insignificant effects, and no study reported negative effects; however, for cognition and language mechanism, negative effects were reported. Conclusion: AOP is likely to have positive effect on performance, code size, modularity, and evolution. However its effect on cognition and language mechanism is less likely to be positive. Care should be taken using AOP outside the context in which it has been validated.

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